In this blog, we will introduce popular AI Agent Frameworks, Benchmarks (keep updated and beyond) Types and provide you some examples with Project Name, Project Website and its application and industries. The resources are collected from AI and ML websites and communities (github, huggingface, paper arxiv,etc) and the comprehensive will keep updating. You can also visit AI Agent Search to find the best resources AI Agents from various industries and applications. For AI Agent Frameworks, we will cover some popular AI agent frameworks, including LangChain, AutoGen, Crew AI etc. And for various types of AI agents, since it's very broad concepts, we will mainly cover the AI agents classified by Autonomous Ability (Auto AI Agents or Rule based) and by industries perspective. For AI Agent Benchmarks, this blog is usefully for AI and ML practitioners and beginners who want to understand what are AI Agents Benchmarks or Environments, the key capability why there are important and how the applications of these AI Agent benchmarks. We will cover different categories of AI Agent Environments, including Game-Based Environments, Text Chat-Based Environments, Physics and Robotics Simulations, Multi-Agent Platforms. Additionally, we can cover AI-Agents in various domains, such as the benchmarks and environments of AI Agents in Healthcare, AI Agents in Finance, AI Agents in Law, AI Agents in Education, etc. To find best AI Agent and Apps Search Engine and Navigation, please visit AI Agent Search.

In this blog, we will introduce a comprehensive list of AI Agents Marketplace Store and Search Portals to watch in 2025. With the rapid development of LLM based AI systems, AI agents is projected to grow tremendously and faster than ever before. There is need for users or enterprise owners to find and navigate the best AI Agents to satisfy their needs, in various industries, for different jobs etc.

In this blog, we will introduce popular AI Agent Frameworks, Benchmarks (keep updated and beyond) Types and provide you some examples with Project Name, Project Website and its application and industries. The resources are collected from AI and ML websites and communities (github, huggingface, paper arxiv,etc) and the comprehensive will keep updating. You can also visit AI Agent Search to find the best resources AI Agents from various industries and applications. For AI Agent Frameworks, we will cover some popular AI agent frameworks, including LangChain, AutoGen, Crew AI etc. And for various types of AI agents, since it's very broad concepts, we will mainly cover the AI agents classified by Autonomous Ability (Auto AI Agents or Rule based) and by industries perspective. For AI Agent Benchmarks, this blog is usefully for AI and ML practitioners and beginners who want to understand what are AI Agents Benchmarks or Environments, the key capability why there are important and how the applications of these AI Agent benchmarks. We will cover different categories of AI Agent Environments, including Game-Based Environments, Text Chat-Based Environments, Physics and Robotics Simulations, Multi-Agent Platforms. Additionally, we can cover AI-Agents in various domains, such as the benchmarks and environments of AI Agents in Healthcare, AI Agents in Finance, AI Agents in Law, AI Agents in Education, etc. To find best AI Agent and Apps Search Engine and Navigation, please visit AI Agent Search.

In this blog, we will introduce popular AI Agent Frameworks, Benchmarks (keep updated and beyond) Types and provide you some examples with Project Name, Project Website and its application and industries. The resources are collected from AI and ML websites and communities (github, huggingface, paper arxiv,etc) and the comprehensive will keep updating. You can also visit AI Agent Search to find the best resources AI Agents from various industries and applications. For AI Agent Frameworks, we will cover some popular AI agent frameworks, including LangChain, AutoGen, Crew AI etc. And for various types of AI agents, since it's very broad concepts, we will mainly cover the AI agents classified by Autonomous Ability (Auto AI Agents or Rule based) and by industries perspective. For AI Agent Benchmarks, this blog is usefully for AI and ML practitioners and beginners who want to understand what are AI Agents Benchmarks or Environments, the key capability why there are important and how the applications of these AI Agent benchmarks. We will cover different categories of AI Agent Environments, including Game-Based Environments, Text Chat-Based Environments, Physics and Robotics Simulations, Multi-Agent Platforms. Additionally, we can cover AI-Agents in various domains, such as the benchmarks and environments of AI Agents in Healthcare, AI Agents in Finance, AI Agents in Law, AI Agents in Education, etc. To find best AI Agent and Apps Search Engine and Navigation, please visit AI Agent Search.

In this blog, we will summarize the latex code for equations of CFA Level I exam, Formula Sheet Equations and Latex Code, and provide Chatbot as AI Assistant to facilitate your reading. You can ask question like what is "Real GDP" in the chatbox. Topics in the blog include three major parts of CFA Level I exam: QUANTITATIVE, ECONOMICS and FINANCIAL REPORTING. Detailed topics include THE TIME VALUE OF MONEY, Future Value, Present Value, Effective Annual Rate, Continuous Compounding, Ordinary Annuity, Annuity Due, Perpetuity, STATISTICAL CONCEPT AND MARKET RETURNS, Fisher Skewness, Kurtosis, Two-asset portfolio, Three-asset portfolio, Microeconomics, Simple Interest, Effective Rate, Future Value of Ordinary Annuities, Annuities Due, Present Value of Ordinary Annuities, Allocative Efficiency Condition, Average Fixed Cost; Macroeconomics Investment, Aggregate Expenditure Without Government or Foreign Sectors, Marginal Propensity to Consume MPC, Marginal Propensity Save MPS, Sum of Marginal Propensity to Save and Marginal Propensity to Consume, Autonomous Spending Multiplier, Balanced Budget Multiplier, Banks Reserve Ratio, Nominal Interest Rate, Real GDP, Real Interest Rate, Tax Multiplier, Unemployment Rate. FINANCIAL REPORTING and ANALYSIS, Basic EPS, Diluted EPS, Balance Sheet, Free Cash Flow to the Firm, Cash Flow Performance Ratio, Cash Flow To Revenue Ratio, Cash Return On Assets, Cash Return On Assets, Cash Return On Equity, Activity Ratio, Inventory Turnover, Days of Inventory On Hand (DOH), Receivables Turnover, Days of Sales Outstanding, etc.

In this blog, we will summarize the latex code of most popular formulas and equations for Economics-MacroEconomics. We will cover important topics, including Investment, Aggregate Expenditure Without Government or Foreign Sectors, Marginal Propensity to Consume MPC, Marginal Propensity Save MPS, Sum of Marginal Propensity to Save and Marginal Propensity to Consume, Autonomous Spending Multiplier, Balanced Budget Multiplier, Banks Reserve Ratio, Budget Deficit, Financial Account Balance, Consumer Price Index CPI, Consumption Function, Current-Account Balance, Equality of Leakages and Injections, Equation of Exchange, Gross Domestic Product GDP, Gross Domestic Product Deflator, Inflation Between Two Years, Merchandise Trade Balance, Nominal Interest Rate, Real GDP, Real Interest Rate, Tax Multiplier, Unemployment Rate, etc.

In this blog, we will summarize the latex code for equations of CFA Level I exam, Formula Sheet Equations and Latex Code, and provide Chatbot as AI Assistant to facilitate your reading. You can ask question like what is "Real GDP" in the chatbox. Topics in the blog include three major parts of CFA Level I exam: QUANTITATIVE, ECONOMICS and FINANCIAL REPORTING. Detailed topics include THE TIME VALUE OF MONEY, Future Value, Present Value, Effective Annual Rate, Continuous Compounding, Ordinary Annuity, Annuity Due, Perpetuity, STATISTICAL CONCEPT AND MARKET RETURNS, Fisher Skewness, Kurtosis, Two-asset portfolio, Three-asset portfolio, Microeconomics, Simple Interest, Effective Rate, Future Value of Ordinary Annuities, Annuities Due, Present Value of Ordinary Annuities, Allocative Efficiency Condition, Average Fixed Cost; Macroeconomics Investment, Aggregate Expenditure Without Government or Foreign Sectors, Marginal Propensity to Consume MPC, Marginal Propensity Save MPS, Sum of Marginal Propensity to Save and Marginal Propensity to Consume, Autonomous Spending Multiplier, Balanced Budget Multiplier, Banks Reserve Ratio, Nominal Interest Rate, Real GDP, Real Interest Rate, Tax Multiplier, Unemployment Rate. FINANCIAL REPORTING and ANALYSIS, Basic EPS, Diluted EPS, Balance Sheet, Free Cash Flow to the Firm, Cash Flow Performance Ratio, Cash Flow To Revenue Ratio, Cash Return On Assets, Cash Return On Assets, Cash Return On Equity, Activity Ratio, Inventory Turnover, Days of Inventory On Hand (DOH), Receivables Turnover, Days of Sales Outstanding, etc.

In this blog, we will summarize the latex code of most popular equations and formulas for Equilibrium, Chemistry. The topics include Acid Ionization Constant, Base Ionization Constant, Relationship of Conjugate Acidâ??Base Pair, Negative Logarithms Relationship of Conjugate Acidâ??base Pair, Buffer Design Equation, Gas Pressure and Concentration Relationship, Ion Product Constant for Water, pH and pOH Relationship, pH Definition, pOH Definition, pKa Definition, pKb Definition, pOH and Base Ionization Equilibrium Constant Relationship.

In this blog, we will summarize the latex code for equations of CFA Level I exam, Formula Sheet Equations and Latex Code, and provide Chatbot as AI Assistant to facilitate your reading. You can ask question like what is "Real GDP" in the chatbox. Topics in the blog include three major parts of CFA Level I exam: QUANTITATIVE, ECONOMICS and FINANCIAL REPORTING. Detailed topics include THE TIME VALUE OF MONEY, Future Value, Present Value, Effective Annual Rate, Continuous Compounding, Ordinary Annuity, Annuity Due, Perpetuity, STATISTICAL CONCEPT AND MARKET RETURNS, Fisher Skewness, Kurtosis, Two-asset portfolio, Three-asset portfolio, Microeconomics, Simple Interest, Effective Rate, Future Value of Ordinary Annuities, Annuities Due, Present Value of Ordinary Annuities, Allocative Efficiency Condition, Average Fixed Cost; Macroeconomics Investment, Aggregate Expenditure Without Government or Foreign Sectors, Marginal Propensity to Consume MPC, Marginal Propensity Save MPS, Sum of Marginal Propensity to Save and Marginal Propensity to Consume, Autonomous Spending Multiplier, Balanced Budget Multiplier, Banks Reserve Ratio, Nominal Interest Rate, Real GDP, Real Interest Rate, Tax Multiplier, Unemployment Rate. FINANCIAL REPORTING and ANALYSIS, Basic EPS, Diluted EPS, Balance Sheet, Free Cash Flow to the Firm, Cash Flow Performance Ratio, Cash Flow To Revenue Ratio, Cash Return On Assets, Cash Return On Assets, Cash Return On Equity, Activity Ratio, Inventory Turnover, Days of Inventory On Hand (DOH), Receivables Turnover, Days of Sales Outstanding, etc.

As a fifth-year PhD student who is graduating soon this year in 2025, I still haven't received any satisfactory job offers. My research interests are in the fields of multi-modal understanding/multimedia but the publications are not among the top tiers (NIPS + ICLR) so there is no way that I can find a job in academia. And my second plan is to find a position as research scientist in large corporations or startups. After several rounds of job finding and a few round of interviews, I found out that the competition is so fierce this year and there are hundreds of applicants aiming at OpenAI, Google Research, FAIR, etc. And I also interviewed with Salesforce, Amazon, etc. But all I got are negative feedback. What can I do and how to help ease my anxiety?

In this blog, we will summarize the latex code of most fundamental equations of multi-task learning(MTL) and transfer learning(TL). Multi-Task Learning aims to optimize N related tasks simultaneously and achieve the overall trade-off between multiple tasks. Typical network structure include shared-bottom models, Cross-Stitch Network, Multi-Gate Mixture of Experts (MMoE), Progressive Layered Extraction (PLE), Entire Space Multi-Task Model (ESSM) models and etc. Different from multi-task learning. In the following sections, we will dicuss more details of MTL equations, which is useful for your quick reference.

In this blog, we will summarize the latex code of equations of Graph Neural Network(GNN) models, which are useful as quick reference for your research. For common notation, we denote G=(V,E) as the graph. V as the set of nodes with size |V|=N, and E as the set of N_e edges as |E| = N_e. A is denoted as the adjacency matrix. For each node v, we use h_v and o_v as hidde state and output vector of each node.

In this blog, we will summarize the latex code for complex variables formulas, including complex numbers, De Moivreâ??s theorem and power series for complex variables e^{z}, sin(z), cos(z), ln(1+z), (1+z)^{n}, etc.